When food and other crops are grown on a large scale, either in protected cultivation (such as in a greenhouse) or outdoors, growers face several challenges. For example, it is generally difficult for a grower to predict the quality and yield of the crop at a stage in crop development when intervention will still be feasible and useful. Also it can be difficult for a grower to know if, where and when the crop has a problem (such as related to a pest, disease, water, other abiotic stress or nutritional deficit), and the extent of the problem, until it is readily visible to human scouts. Often by that stage it may require expensive and extensive intervention. Crop yield is affected by the physiological performance of the crop throughout its development cycle, which is in turn dependent on external environmental factors among other things. Precise intervention at critical developmental stages, can allow growers to achieve high or optimum yields of the crop. Pest and disease problems are often exacerbated by the large scale on which some crops are grown, the costs for labor, and the speed and ease with which pests and diseases can spread, especially in protected cultivation. When it comes to monitoring crops for pests, diseases and other deleterious conditions, a common approach has been the use of human scouts who visually inspect the crop. However, human scouts whose role it is to locate plants with pests, diseases or other problems, can themselves facilitate the spread of those pests and diseases, for example, through their physical contact with multiple plants and the resulting transfer of pests or diseases from plant to plant. Other limitations of using human scouts for crop monitoring include the speed with which they can cover a large area, and variation in interpretation among individual humans. They also require specific training, and performance of even a diligent employee will be subjective and vary over time.
Many crop management practices are employed prophylactically or simply based on past practices and customs. A common underlying assumption is that crops are uniform and perform evenly which is not necessarily the case, for example, because plants respond to differences in microclimate on a finer scale.
Sensor systems have been developed for crop monitoring, but many of these systems have limitations and shortcomings. For example, some systems use a grid of sensors suspended above the crop (in a zone, usually about an acre in greenhouses) or that fly over the crops. Such sensory grids can be used to monitor environmental conditions or general responses from plants, but generally this is on a course-grained scale. Handheld devices can be used to capture data from individual plants, but these devices tend to be cumbersome to use, and data is captured only from plants that the operator of the handheld device interacts with directly. It is generally not feasible to use a handheld device to capture data from all plants within an area being managed. Often such devices are used by clipping them to the plant or otherwise contacting the plant with the sensing device. Other systems rely on visual detection of causal factors (e.g. pests or disease) by means of motion detection or visual pattern recognition. Visual detection devices can be technologically taxing and economically unfeasible. Additionally, in certain cases, significant damage has already been done to the crop by the time the causal factor is visually identified.
Some sensory devices/systems are geared toward specific indicators (presence of disease, anthocyanin content, emergence of adult pests, etc.) with narrow spectra of responses, often using sensors that function during daylight hours. These technologies are generally large and expensive, and require a human operator, and some of them are time-consuming. For example, fluorescent measurement systems have been used to detect far red spectra produced by plants when exposed to blue or red light. Conventional fluorescent measurement requires complex equipment, and typically a single assessment takes several minutes and sometimes up to about 15 minutes to complete. Other sensory systems can collect very general information (temperature, humidity) that cannot accurately pinpoint problems at the level of individual plants, or at levels of sensitivity that convey timely information in real time.
Expert growers develop a wealth of knowledge and experience by working their crop for multiple years. When currently available, highly automated sensor-based crop monitoring systems are used, the valuable expertise and insight of an experienced grower is no longer effectively harnessed. Furthermore, although humans and existing sensory systems for crop monitoring may, to some degree, be able to identify problems with a crop, they are not capable of predicting the future health of a crop or plant.